An optimal weight learning machine for handwritten digit image recognition

@article{Man2013AnOW,
  title={An optimal weight learning machine for handwritten digit image recognition},
  author={Zhihong Man and Kevin Lee and Dianhui Wang and Zhenwei Cao and Suiyang Khoo},
  journal={Signal Process.},
  year={2013},
  volume={93},
  pages={1624-1638}
}
An optimal weight learning machine for a single-hidden layer feedforward network (SLFN) with the application to handwritten digit image recognition is developed in this paper. It is seen that both the input weights and the output weights of the SLFN are globally optimized with the batch learning type of least squares. All feature vectors of the classifier can then be placed at the prescribed positions in the feature space in the sense that the separability of all nonlinearly separable patterns… CONTINUE READING

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